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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 9-RES-JB
    11. 5833
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    Explanations

    phrases related to earning, achieving, or acquiring something

    oai_token-act-pair · gpt-3.5-turbo

    terms related to earning or obtaining something, particularly in a financial context

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     illum
    -0.70
    dating
    -0.64
    yrus
    -0.64
    ary
    -0.64
    haus
    -0.63
    irez
    -0.62
    MRI
    -0.61
     densely
    -0.61
     resize
    -0.58
    olver
    -0.58
    POSITIVE LOGITS
     certificates
    0.94
     accol
    0.86
     badges
    0.84
    hardt
    0.83
     laure
    0.82
     credits
    0.77
     renown
    0.75
     credit
    0.74
     applause
    0.73
     distinctions
    0.73
    Activations Density 0.032%

    No Known Activations